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AI Resume Analyzer
NLP-Based ATS Resume Analysis Platform
A smart assistant for building standout resumes: upload a resume and NLP assesses skills, identifies gaps and delivers personalised certification, course and tutorial recommendations.
Overview
The analyzer parses an uploaded resume, extracts entities and skills, scores it against target-role expectations, then recommends the specific learning that closes the biggest gaps.
Problem Statement
Candidates get rejected by ATS filters without ever knowing which skills or keywords were missing, and generic advice does not tell them what to learn next.
Architecture
- ›Python parsing layer for PDF and DOCX extraction
- ›NLP pipeline for entity, skill and keyword extraction
- ›Role-profile scoring engine comparing candidate skills to target roles
- ›Recommendation engine mapping gaps to certifications, courses and videos
- ›Streamlit interface for upload and reporting
Workflow
- 01Upload a resume
- 02Text and structure extraction
- 03NLP skill and keyword analysis
- 04Gap scoring against the chosen role profile
- 05Personalised learning recommendations rendered as a report
Features
- ✦Analyzes uploaded resumes with NLP
- ✦Tailored suggestions: certifications, courses and tutorials
- ✦Skill-gap scoring against industry role profiles
- ✦Guides targeted skill development so candidates stand out
Technology Stack
NLPPythonStreamlitspaCyPandas
Challenges & Solutions
Resume layouts break naive text extraction.
SOLUTION · Normalised multi-column and table layouts before running the NLP pipeline.
Skill names appear in dozens of variants.
SOLUTION · Built a synonym-aware skill dictionary to canonicalise extracted entities.
Generic advice is not actionable.
SOLUTION · Mapped every detected gap to a specific certification, course or tutorial.
Results
- →Instant, structured feedback instead of silent ATS rejection
- →Concrete learning path generated per candidate
- →Reusable role-profile system for new job families
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